Research Data Engineering

AI in the EGI e-infrastructure -- Past experiences and future strategies

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Key Insights

  • The EGI Federation has provided federated e-infrastructure services to European and global science for over 15 years.
  • We review EGI's early experiences with AI in the interTwin and iMagine Horizon Eur.
Cite this synthesis DOI: 10.48550/arXiv.2610.40494 ↗
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@misc{ acaciadata-research-ai-in-the-egi-e-infrastructure-past-experiences-and-future-s,
  title = { AI in the EGI e-infrastructure -- Past experiences and future strategies },
  author = { Leszek },
  year = { 2026 },
  doi = { 10.48550/arXiv.2610.40494 },
  url = { http://arxiv.org/abs/2610.40494v1 },
  note = {Summarized and classified by AcaciaFund}
}
TY  - GEN
TI  - AI in the EGI e-infrastructure -- Past experiences and future strategies
AU  - Leszek
PY  - 2026
DO  - 10.48550/arXiv.2610.40494
UR  - http://arxiv.org/abs/2610.40494v1
ER  -

Edit on GitHub — registry.json

Overview

The EGI Federation has provided federated e-infrastructure services to European and global science for over 15 years. We review EGI's early experiences with AI in the interTwin and iMagine Horizon Eur

Key Topics

  • Distributed Computing: A theme covered by this item within the data engineering context.

Why It Matters

This item adds to the data engineering knowledge base. Practitioners can use it to stay current on AI in the EGI e-infrastructure -- Past experiences and future strategies, but should validate its claims against primary sources and more recent work before relying on it in production decisions.

Key Takeaways

  • Understand how AI in the EGI e-infrastructure -- Past experiences and future strategies relates to data engineering workflows and controls.
  • Assess evidence quality and freshness before acting on the findings.
  • Use the tagged topics to connect this item to related content in the library.
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